Dynamic NLR and PLR in predicting Covid-19 severity: a retrospective cohort study (preprint)

Background: the hyperinflammation phase of severe SARS-CoV-2 is characterized by complete blood count alterations. In this context, the neutrophil to lymphocyte ratio (NLR) and the platelet to lymphocyte ratio (PLR) can be used as prognostic factors. We study NLR and PLR trends at different timepoints and compute optimal cutoffs to predict four outcomes: use of Continuous Positive Airways Pressure (CPAP), ICU admission, invasive ventilation and death. Methods: we retrospectively included all adult patients with SARS-CoV-2 pneumonia admitted from 23rd January 2020 to 18th May 2021. Data were extracted using ICD9 codes and our Covid-19 registry. Analyses included descriptive statistics and non parametric tests to study the ability of NLR and PLR to distinguish the patients’ outcomes at each timepoint. ROC curves were built for NLR and PLR at each timepoint (minus discharge) in order to identify cutoffs to distinguish severe and non severe disease and their statistical significance was assessed with the Chi-square test. NLR and PLR were compared with DeLong’s test. Results: we included 2169 patients. NLR and PLR were higher in severe Covid-19 at all the timepoints, with a difference that gets bigger and a trend that is steeper in more severe disease. Both ratios were able to distinguish the outcomes at each timepoint. For NLR, the areas under the curve (AUROC) ranged between 0.59 and 0.81, for PLR, between 0.53 and 0.67. From each ROC curve we computed an optimal cutoff value (e.g. NLR 7 for CPAP for males at admission). NLR performed better than PLR. Conclusion: our results are in line with other studies that computed NLR and PLR trends and values in disease, especially with those that distinguished between different grades of severity. Our study is retrospective and single centre, and is limited by selection bias, but includes more than 2000 patients, thus limiting the confounding factors and outliers. Our cutoffs do not only deal with severity and mortality but allow for a more tailored approach. Future prospect include validating our cutoffs in a prospective cohort and comparing their performance against other Covid19 scores. 

Immunity to SARS-CoV-2 up to 15 months after infection (preprint)

Background: Information concerning the longevity of immunity to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) following natural infection may have considerable implications for durability of immunity induced by vaccines. Here, we monitored the SARS-CoV-2 specific immune response in convalescent coronavirus disease-2019 (COVID-19) patients up to 15 months after symptoms onset. Methods: The levels of anti-spike and anti-receptor binding domain antibodies and neutralizing activities were tested in a total of 188 samples from 136 convalescent patients who experience mild to critical COVID-19. Specific memory B and T cell responses were measured in 76 peripheral blood mononuclear cell samples collected from 54 patients. Twenty-three vaccinated individuals were included for comparison. Findings: Following a peak at day 15-28 post-infection, the IgG antibody response and plasma neutralizing titers gradually decreased over time but stabilized after 6 months. Plasma neutralizing activity against G614 was still detected in 87% of the patients at 6-15 months. Compared to G614, the median neutralizing titers against Beta, Gamma and Delta variants in plasma collected at early (15-103 days) and late (9-15 month) convalescence were 16- and 8-fold lower, respectively. SARS-CoV-2-specific memory B and T cells reached a peak at 3-6 months and persisted in the majority of patients up to 15 months although a significant decrease in specific T cells was observed between 6 and 15 months. Conclusion: The data suggest that antiviral specific immunity especially memory B cells in COVID-19 convalescent patients is long-lasting, but some variants of concern, including the fast-spreading Delta variant, may at least partially escape the neutralizing activity of plasma antibodies. Funding: EU-ATAC consortium, the Italian Ministry of Health, the Swedish Research Council, SciLifeLab, and KAW.

Persistence of SARS-CoV-2 specific B- and T-cell responses in convalescent COVID-19 patients 6-8 months after the infection (preprint)

Background: The longevity of the immune response against SARS-CoV-2 is currently debated. We thus profiled the serum anti-SARS-CoV-2 antibody levels and virus specific memory B- and T-cell responses over time in convalescent COVID-19 patients. Methods: A cohort of COVID-19 patients from the Lombardy region in Italy who experienced mild to critical disease and Swedish volunteers with mild symptoms, were tested for the presence of elevated anti-spike and anti-receptor binding domain antibody levels over a period of eight months. In addition, specific memory B- and T-cell responses were tested in selected patient samples. Results: Anti-SARS-CoV-2 antibodies were present in 85% samples collected within 4 weeks after onset of symptoms in COVID-19 patients. Levels of specific IgM or IgA antibodies declined after 1 month while levels of specific IgG antibodies remained stable up to 6 months after diagnosis. Anti-SARS-CoV-2 IgG antibodies were still present, though at a significantly lower level, in 80% samples collected at 6-8 months after symptom onset. SARS-CoV-2-specific memory B- and T-cell responses were developed in vast majority of the patients tested, regardless of disease severity, and remained detectable up to 6-8 months after infection. Conclusions: Although the serum levels of anti-SARS-CoV-2 IgG antibodies started to decline, virus-specific T and/or memory B cell responses increased with time and maintained during the study period (6-8 months after infection).

In-hospital mortality from Coronavirus Disease 2019 in a northern Italian centre:results of a competing risk analysis from SMAtteo COvid19 REgistry (SMACORE) (preprint)

Objectives An accurate prediction of the clinical outcomes of European patients requiring hospitalisation for Coronavirus Disease 2019 (COVID-19) is lacking. The aim of the study is to identify predictors of in-hospital mortality and discharge in a cohort of Lombardy patients with COVID-19. MethodsAll consecutive hospitalised patients from February 21stto March 30th, 2020, with confirmed COVID-19 from the IRCCS Policlinico San Matteo, Pavia, Lombardy, Italy, were included. In-hospital mortality and discharge were evaluated by competing risk analysis. The Fine and Gray model was fitted in order to estimate the effect of covariates on the cumulative incidence functions (CIFs) for in-hospital mortality and discharge.Results 426 adult patients (median age 68 (IQR, 56 to 77 years) were admitted with confirmed COVID-19 over a 5-week period; 292 (69%) were male. By 21 April 2020, 141 (33%) of these patients had died, 239 (56%) patients had been discharged and 46 (11%) were still hospitalised. Regression on the CIFs for in-hospital mortality showed that older age, male sex, number of comorbidities and hospital admission after March 4thwere independent risk factors associated with in-hospital mortality.Conclusions Olderage, male sex and number of comorbidities definitively predicted in-hospital mortality in hospitalised patients with COVID-19